Study on Sliding Mode Control with RBF Network for DSTATCOM

Abstract

For the problems of parameters disturbance, nonlinear and uncertainty of distribution static compensator (DSTATCOM), this paper studies on sliding mode control based on radial basis function (RBF) network. The fast tracking of DSTATCOM reactive current is achieved by using of RBF neural networks and equivalent sliding mode control. The method has a strong adaptability and robustness for load disturbances and system parameters change, and integrates the advantages of neural network and sliding mode control, so it is an ideal intelligent control strategy .The MATLAB simulation results show that the controller has good dynamic and static quality, and provides an effective way for improving the performance of DSTATCOM.

Comprehensive Review of Distributed FACTS Control Algorithms for Power Quality Enhancement in Utility Grid With Renewable Energy Penetration

“…Apart from the algorithms mentioned in the above section, the other conventional control algorithms have played an important role in PQ mitigation with DFACTS devices. These includes, power balance control [102], instantaneous symmetrical components control [103], sliding mode control (SMC) [104], average unit power factor control [105], voltage template and PI controller [106], PLL based control [107] and their modified methods. However, the experimental framework for conventional control algorithms has not been extensively used with RE penetration in the utility grid.…”